Abstract:
Multilateral peace operations are increasingly confronting a set of interrelated and mutually reinforcing security challenges that are relatively new to them, that do not respect borders, and that have causes and effects which cut right across the international security, peacebuilding and development agendas. As a result, the New Geopolitics of Peace Operations III: Non‑Traditional Security Challenges initiative seeks to enhance understanding about peace operations and non-traditional security challenges such as terrorism and violent extremism, irregular migration, piracy, organized crime and environmental degradation. As a part of this initiative, this SIPRI Background Paper explores the ‘non-traditional’ security challenges that organized crime presents to multilateral peace operations.

Abstract:
The United States remains committed to its role as a global leader on humanitarian issues and will continue seeking to avert crises that spawn the need for humanitarian aid, Deputy Secretary of State John Sullivan said.

Abstract:
Th e reaction of the Arab armies to the 2011 uprisings is a subject
that has been frequently examined, but the evolution and reform of
Arab armies is a neglected topic.2
In times of global interdependence,
the Atlantic Alliance must be ready to understand and interact with
a changing Middle East, since NATO Arab partners’ security is more
and more NATO’s security, in terms of shared objectives, common
threats and cooperative security. Arab armies have entered a new
era: traditional obstacles to military reform, mostly due to their
politicization, persist; other variables emerge from the interaction of
domestic, foreign and transnational threats.

Abstract:
Since the financial crisis, EU countries' economies have recovered to the point that they are exiting their adjustment programmes. Institutional stability mechanisms have been improved at the European level, with the promotion of the banking union and the establishment of a European Monetary Fund, for instance. However, the authors argue that such crisis contingencies should include markets in their risk-sharing, which would require better coordination with institutions.

Abstract:
Many datasets use experts to code latent quantities of interest. However, scholars have not explored either the factors affecting expert reliability or the degree to which these factors influence estimates of latent concepts. Here we systematically analyze potential correlates of expert reliability using six randomly selected variables from a cross-national panel dataset, V-Dem v8. The V-Dem project includes a diverse group of over 3,000 experts and uses an IRT model to incorporate variation in both expert reliability and scale perception into its data aggregation process. In the process, the IRT model produces an estimate of expert reliability, which affects the relative contribution of an expert to the model. We examine a variety of factors that could correlate with reliability, and find little evidence of theoretically-untenable bias due to expert characteristics. On the other hand, there is evidence that attentive and condent experts who have a basic contextual knowledge of the concept of democracy are more reliable.

Abstract:
Repeated measurements of the same countries, people, or groups over time are vital to many fields of political science. These measurements, sometimes called time-series cross-sectional (TSCS) data, allow researchers to estimate a broad set of causal quantities, including contemporaneous and lagged treatment effects. Unfortunately, popular methods for TSCS data can only produce valid inferences for lagged effects under very strong assumptions. In this paper, we use potential outcomes to define causal quantities of interest in this settings and clarify how standard models like the autoregressive distributed lag model can produce biased estimates of these quantities due to post-treatment conditioning. We then describe two estimation strategies that avoid these post-treatment biases—inverse probability weighting and structural nested mean models—and show via simulations that they can outperform standard approaches in small sample settings. We illustrate these methods in a study of how welfare spending affects terrorism.

Abstract:
The study of popular support for authoritarian regimes, and the comparative study of political attitudes, has long relied on the assumption that survey respondents provide truthful answers on surveys. However, when measuring regime support in closed political systems there is a distinct risk that individuals are less than forthright due to fear that their opinions may be made known to the public or the authorities. In order to test this assumption, we conducted a novel web-based survey in China in which we included four list experiments of commonly used items in the comparative literature on regime support. We find systematic bias for all four measures as a result of selfcensorship; substantially more individuals state that they support the regime with direct questioning than do when presented with our anonymous, indirect list experiments. The level of self-censorship, which ranges from 16 to 22 percentage points, is considerably higher than previously thought. Selfcensorship is further most prevalent among the wealthy, urban, female and younger respondents. These findings indicate that prior studies that have found high levels of support for the Chinese regime using these particular measures likely overestimate the true level of support. Further, crossnational studies which compare popular support across regime type may be systematically biased if responses are not subject to the same level of falsification across regime types.

Abstract:
The Historical Varieties of Democracy Dataset (Historical V-Dem) is a new dataset containing about 260 indicators, both factual and evaluative, describing various aspects of political regimes and state institutions. The dataset covers 91 polities globally – including most large, sovereign states, as well as some semi-sovereign entities and large colonies – from 1789 to 1920 for many cases. The majority of the indicators are also included in the Varieties of Democracy dataset, which covers the period from 1900 to the present – and together these two datasets cover the bulk of “modern history”. Historical V-Dem also includes several new indicators, covering features that are pertinent for 19thcentury polities. We describe the data, the process of coding, and the different strategies employed in Historical V-Dem to cope with issues of reliability and validity and ensure inter-temporal- and cross-country comparability. To illustrate the potential uses of the dataset we provide a descriptive account of patterns of democratization in the “long 19th century.” Finally, we perform an empirical investigation of how inter-state war relates to subsequent democratization.

Abstract:
The democratic peace is one of the most robust findings in international relations. Yet it suffers from two important limitations. First, even those who fully embrace the democratic peace have difficulty precisely identifying which facet of democracy drives the result. Second, the vast majority of studies have relied on a single measure of democracy – the Polity index. This paper reassesses interstate conflict on several new measures of democracy and their disaggregated components from the Varieties of Democracy project in a global sample of 173 countries from 1900–2010 (www.v-dem.net). We theorize three distinct mechanisms of constraint that may explain why some countries do not engage in military conflict with each other: formal vertical (e.g. elections), informal vertical (e.g. civil society activism), and horizontal accountability (e.g. interbranch constraint on the executive). We find that the formal vertical channels of accountability provided by elections are not as crucial as horizontal constraint and the informal vertical accountability provided by a strong civil society.

Abstract:
Sometimes the normal course of events is disrupted by a particularly swift and profound change. Historians have often referred to such changes as "revolutions" and, though they have identied many of them, they have rarely supported their claims with statistical evidence. Here we present a method to identify revolutions based on a measure of the multivariate rate of change called Foote Novelty. We dene revolutions as those periods of time when the value of this measure, F, can, by a non-parametric test, be shown to be signicantly greater than the background rate. Our method also identies conservative periods when the rate of change is unusually low. Importantly, our method permits searching for revolutions over any time scale that the data permit. We apply it to several quantitative data sets that capture long-term political, social and cultural changes and, in some of them, identify revolutions, both well known and not. Our method is a general one that can be applied to any phenomenon captured by multivariate time series data of sufficient quality.